diff --git a/model_zoo/official/nlp/mass/README.md b/model_zoo/official/nlp/mass/README.md index c5f3694b244..134c4de70c8 100644 --- a/model_zoo/official/nlp/mass/README.md +++ b/model_zoo/official/nlp/mass/README.md @@ -26,6 +26,10 @@ - [Pre-training](#pre-training) - [Fine-tuning](#fine-tuning) - [Inference](#inference) + - [Mindir Inference Process](#mindir-inference-process) + - [Export MindIR](#export-mindir) + - [Infer on Ascend310](#infer-on-ascend310) + - [result](#result) - [Performance](#performance) - [Results](#results) - [Fine-Tuning on Text Summarization](#fine-tuning-on-text-summarization) @@ -587,6 +591,33 @@ You can also run the shell script `run_gpu.sh` on gpu as followed: sh run_gpu.sh -t i -n 1 -i 1 -c config/config.json -o {outputfile} ``` +## Mindir Inference Process + +### [Export MindIR](#contents) + +```shell +python export.py --ckpt_file [CKPT_PATH] --file_name [FILE_NAME] --file_format [FILE_FORMAT] +``` + +The ckpt_file parameter is required, +`EXPORT_FORMAT` should be in ["AIR", "MINDIR"] + +### Infer on Ascend310 + +Before performing inference, the mindir file must be exported by `export.py` script. We only provide an example of inference using MINDIR model. + +```shell +# Ascend310 inference +bash run_infer_310.sh [MINDIR_PATH] [CONFIG] [VOCAB] [OUTPUT] [NEED_PREPROCESS] [DEVICE_ID] +``` + +- `NEED_PREPROCESS` means weather need preprocess or not, it's value is 'y' or 'n'. +- `DEVICE_ID` is optional, default value is 0. + +### result + +Inference result is saved in current path, you can find result in acc.log file. + # Performance ## Results diff --git a/model_zoo/official/nlp/mass/README_CN.md b/model_zoo/official/nlp/mass/README_CN.md index 44df5224496..de8f2f741d8 100644 --- a/model_zoo/official/nlp/mass/README_CN.md +++ b/model_zoo/official/nlp/mass/README_CN.md @@ -27,6 +27,10 @@ - [预训练](#预训练) - [微调](#微调) - [推理](#推理) + - [Mindir推理](#Mindir推理) + - [导出模型](#导出模型) + - [在Ascend310执行推理](#在Ascend310执行推理) + - [结果](#结果) - [性能](#性能) - [结果](#结果) - [文本摘要微调](#文本摘要微调) @@ -586,6 +590,33 @@ sh run_ascend.sh -t i -n 1 -i 1 -c config/config.json -o {outputfile} sh run_gpu.sh -t i -n 1 -i 1 -c config/config.json -o {outputfile} ``` +## Mindir推理 + +### [导出模型](#contents) + +```shell +python export.py --ckpt_file [CKPT_PATH] --file_name [FILE_NAME] --file_format [FILE_FORMAT] +``` + +参数ckpt_file为必填项， +`EXPORT_FORMAT` 必须在 ["AIR", "MINDIR"]中选择。 + +### 在Ascend310执行推理 + +在执行推理前，mindir文件必须通过`export.py`脚本导出。以下展示了使用minir模型执行推理的示例。 + +```shell +# Ascend310推理 +bash run_infer_310.sh [MINDIR_PATH] [CONFIG] [VOCAB] [OUTPUT] [NEED_PREPROCESS] [DEVICE_ID] +``` + +- `NEED_PREPROCESS` 表示数据是否需要预处理，取值范围为：'y' 或者 'n'。 +- `DEVICE_ID` 可选，默认值为0。 + +### 结果 + +推理结果保存在脚本执行的当前路径，精度计算结果可以在acc.log中看到。 + # 性能 ## 结果 diff --git a/model_zoo/official/nlp/mass/ascend310_infer/CMakeLists.txt b/model_zoo/official/nlp/mass/ascend310_infer/CMakeLists.txt new file mode 100644 index 00000000000..ee3c8544734 --- /dev/null +++ b/model_zoo/official/nlp/mass/ascend310_infer/CMakeLists.txt @@ -0,0 +1,14 @@ +cmake_minimum_required(VERSION 3.14.1) +project(Ascend310Infer) +add_compile_definitions(_GLIBCXX_USE_CXX11_ABI=0) +set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O0 -g -std=c++17 -Werror -Wall -fPIE -Wl,--allow-shlib-undefined") +set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/) +option(MINDSPORE_PATH "mindspore install path" "") +include_directories(${MINDSPORE_PATH}) +include_directories(${MINDSPORE_PATH}/include) +include_directories(${PROJECT_SRC_ROOT}) +find_library(MS_LIB libmindspore.so ${MINDSPORE_PATH}/lib) +file(GLOB_RECURSE MD_LIB ${MINDSPORE_PATH}/_c_dataengine*) + +add_executable(main src/main.cc src/utils.cc) +target_link_libraries(main ${MS_LIB} ${MD_LIB} gflags) diff --git a/model_zoo/official/nlp/mass/ascend310_infer/build.sh b/model_zoo/official/nlp/mass/ascend310_infer/build.sh new file mode 100644 index 00000000000..285514e19f2 --- /dev/null +++ b/model_zoo/official/nlp/mass/ascend310_infer/build.sh @@ -0,0 +1,29 @@ +#!/bin/bash +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================ +if [ -d out ]; then + rm -rf out +fi + +mkdir out +cd out || exit + +if [ -f "Makefile" ]; then + make clean +fi + +cmake .. \ + -DMINDSPORE_PATH="`pip3.7 show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`" +make diff --git a/model_zoo/official/nlp/mass/ascend310_infer/inc/utils.h b/model_zoo/official/nlp/mass/ascend310_infer/inc/utils.h new file mode 100644 index 00000000000..efebe03a8c1 --- /dev/null +++ b/model_zoo/official/nlp/mass/ascend310_infer/inc/utils.h @@ -0,0 +1,32 @@ +/** + * Copyright 2021 Huawei Technologies Co., Ltd + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#ifndef MINDSPORE_INFERENCE_UTILS_H_ +#define MINDSPORE_INFERENCE_UTILS_H_ + +#include +#include +#include +#include +#include +#include "include/api/types.h" + +std::vector GetAllFiles(std::string_view dirName); +DIR *OpenDir(std::string_view dirName); +std::string RealPath(std::string_view path); +mindspore::MSTensor ReadFileToTensor(const std::string &file); +int WriteResult(const std::string& imageFile, const std::vector &outputs); +#endif diff --git a/model_zoo/official/nlp/mass/ascend310_infer/src/main.cc b/model_zoo/official/nlp/mass/ascend310_infer/src/main.cc new file mode 100644 index 00000000000..61b08344f97 --- /dev/null +++ b/model_zoo/official/nlp/mass/ascend310_infer/src/main.cc @@ -0,0 +1,137 @@ +/** + * Copyright 2021 Huawei Technologies Co., Ltd + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include "include/api/model.h" +#include "include/api/context.h" +#include "include/api/types.h" +#include "include/api/serialization.h" +#include "include/dataset/execute.h" +#include "include/dataset/vision.h" +#include "inc/utils.h" + +using mindspore::Context; +using mindspore::Serialization; +using mindspore::Model; +using mindspore::Status; +using mindspore::MSTensor; +using mindspore::dataset::Execute; +using mindspore::ModelType; +using mindspore::GraphCell; +using mindspore::kSuccess; + +DEFINE_string(mindir_path, "", "mindir path"); +DEFINE_string(input0_path, ".", "input0 path"); +DEFINE_string(input1_path, ".", "input1 path"); +DEFINE_int32(device_id, 0, "device id"); + +int main(int argc, char **argv) { + gflags::ParseCommandLineFlags(&argc, &argv, true); + if (RealPath(FLAGS_mindir_path).empty()) { + std::cout << "Invalid mindir" << std::endl; + return 1; + } + + auto context = std::make_shared(); + auto ascend310 = std::make_shared(); + ascend310->SetDeviceID(FLAGS_device_id); + ascend310->SetPrecisionMode("allow_fp32_to_fp16"); + ascend310->SetOpSelectImplMode("high_precision"); + context->MutableDeviceInfo().push_back(ascend310); + mindspore::Graph graph; + Serialization::Load(FLAGS_mindir_path, ModelType::kMindIR, &graph); + + Model model; + Status ret = model.Build(GraphCell(graph), context); + if (ret != kSuccess) { + std::cout << "ERROR: Build failed." << std::endl; + return 1; + } + + std::vector model_inputs = model.GetInputs(); + if (model_inputs.empty()) { + std::cout << "Invalid model, inputs is empty." << std::endl; + return 1; + } + + auto input0_files = GetAllFiles(FLAGS_input0_path); + auto input1_files = GetAllFiles(FLAGS_input1_path); + + if (input0_files.empty() || input1_files.empty()) { + std::cout << "ERROR: input data empty." << std::endl; + return 1; + } + + std::map costTime_map; + size_t size = input0_files.size(); + + for (size_t i = 0; i < size; ++i) { + struct timeval start = {0}; + struct timeval end = {0}; + double startTimeMs; + double endTimeMs; + std::vector inputs; + std::vector outputs; + std::cout << "Start predict input files:" << input0_files[i] << std::endl; + + auto input0 = ReadFileToTensor(input0_files[i]); + auto input1 = ReadFileToTensor(input1_files[i]); + inputs.emplace_back(model_inputs[0].Name(), model_inputs[0].DataType(), model_inputs[0].Shape(), + input0.Data().get(), input0.DataSize()); + inputs.emplace_back(model_inputs[1].Name(), model_inputs[1].DataType(), model_inputs[1].Shape(), + input1.Data().get(), input1.DataSize()); + + gettimeofday(&start, nullptr); + ret = model.Predict(inputs, &outputs); + gettimeofday(&end, nullptr); + if (ret != kSuccess) { + std::cout << "Predict " << input0_files[i] << " failed." << std::endl; + return 1; + } + startTimeMs = (1.0 * start.tv_sec * 1000000 + start.tv_usec) / 1000; + endTimeMs = (1.0 * end.tv_sec * 1000000 + end.tv_usec) / 1000; + costTime_map.insert(std::pair(startTimeMs, endTimeMs)); + WriteResult(input0_files[i], outputs); + } + double average = 0.0; + int inferCount = 0; + + for (auto iter = costTime_map.begin(); iter != costTime_map.end(); iter++) { + double diff = 0.0; + diff = iter->second - iter->first; + average += diff; + inferCount++; + } + average = average / inferCount; + std::stringstream timeCost; + timeCost << "NN inference cost average time: "<< average << " ms of infer_count " << inferCount << std::endl; + std::cout << "NN inference cost average time: "<< average << "ms of infer_count " << inferCount << std::endl; + std::string fileName = "./time_Result" + std::string("/test_perform_static.txt"); + std::ofstream fileStream(fileName.c_str(), std::ios::trunc); + fileStream << timeCost.str(); + fileStream.close(); + costTime_map.clear(); + return 0; +} diff --git a/model_zoo/official/nlp/mass/ascend310_infer/src/utils.cc b/model_zoo/official/nlp/mass/ascend310_infer/src/utils.cc new file mode 100644 index 00000000000..c947e4d5f45 --- /dev/null +++ b/model_zoo/official/nlp/mass/ascend310_infer/src/utils.cc @@ -0,0 +1,129 @@ +/** + * Copyright 2021 Huawei Technologies Co., Ltd + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#include +#include +#include +#include "inc/utils.h" + +using mindspore::MSTensor; +using mindspore::DataType; + +std::vector GetAllFiles(std::string_view dirName) { + struct dirent *filename; + DIR *dir = OpenDir(dirName); + if (dir == nullptr) { + return {}; + } + std::vector res; + while ((filename = readdir(dir)) != nullptr) { + std::string dName = std::string(filename->d_name); + if (dName == "." || dName == ".." || filename->d_type != DT_REG) { + continue; + } + res.emplace_back(std::string(dirName) + "/" + filename->d_name); + } + std::sort(res.begin(), res.end()); + for (auto &f : res) { + std::cout << "image file: " << f << std::endl; + } + return res; +} + +int WriteResult(const std::string& imageFile, const std::vector &outputs) { + std::string homePath = "./result_Files"; + for (size_t i = 0; i < outputs.size(); ++i) { + size_t outputSize; + std::shared_ptr netOutput; + netOutput = outputs[i].Data(); + outputSize = outputs[i].DataSize(); + int pos = imageFile.rfind('/'); + std::string fileName(imageFile, pos + 1); + fileName.replace(fileName.find('.'), fileName.size() - fileName.find('.'), '_' + std::to_string(i) + ".bin"); + std::string outFileName = homePath + "/" + fileName; + FILE * outputFile = fopen(outFileName.c_str(), "wb"); + fwrite(netOutput.get(), outputSize, sizeof(char), outputFile); + fclose(outputFile); + outputFile = nullptr; + } + return 0; +} + +mindspore::MSTensor ReadFileToTensor(const std::string &file) { + if (file.empty()) { + std::cout << "Pointer file is nullptr" << std::endl; + return mindspore::MSTensor(); + } + + std::ifstream ifs(file); + if (!ifs.good()) { + std::cout << "File: " << file << " is not exist" << std::endl; + return mindspore::MSTensor(); + } + + if (!ifs.is_open()) { + std::cout << "File: " << file << "open failed" << std::endl; + return mindspore::MSTensor(); + } + + ifs.seekg(0, std::ios::end); + size_t size = ifs.tellg(); + mindspore::MSTensor buffer(file, mindspore::DataType::kNumberTypeUInt8, {static_cast(size)}, nullptr, size); + + ifs.seekg(0, std::ios::beg); + ifs.read(reinterpret_cast(buffer.MutableData()), size); + ifs.close(); + + return buffer; +} + + +DIR *OpenDir(std::string_view dirName) { + if (dirName.empty()) { + std::cout << " dirName is null ! " << std::endl; + return nullptr; + } + std::string realPath = RealPath(dirName); + struct stat s; + lstat(realPath.c_str(), &s); + if (!S_ISDIR(s.st_mode)) { + std::cout << "dirName is not a valid directory !" << std::endl; + return nullptr; + } + DIR *dir; + dir = opendir(realPath.c_str()); + if (dir == nullptr) { + std::cout << "Can not open dir " << dirName << std::endl; + return nullptr; + } + std::cout << "Successfully opened the dir " << dirName << std::endl; + return dir; +} + +std::string RealPath(std::string_view path) { + char realPathMem[PATH_MAX] = {0}; + char *realPathRet = nullptr; + realPathRet = realpath(path.data(), realPathMem); + + if (realPathRet == nullptr) { + std::cout << "File: " << path << " is not exist."; + return ""; + } + + std::string realPath(realPathMem); + std::cout << path << " realpath is: " << realPath << std::endl; + return realPath; +} diff --git a/model_zoo/official/nlp/mass/postprocess.py b/model_zoo/official/nlp/mass/postprocess.py new file mode 100644 index 00000000000..09e6e2af36e --- /dev/null +++ b/model_zoo/official/nlp/mass/postprocess.py @@ -0,0 +1,99 @@ +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================ +"""Evaluation api.""" +import os +import argparse +import pickle +import numpy as np + + + +from config import TransformerConfig +from src.utils import Dictionary +from src.utils import get_score + +parser = argparse.ArgumentParser(description='postprocess.') +parser.add_argument("--config", type=str, required=True, + help="Model config json file path.") +parser.add_argument("--vocab", type=str, required=True, + help="Vocabulary to use.") +parser.add_argument("--output", type=str, required=True, + help="Result file path.") +parser.add_argument("--metric", type=str, default='rouge', + help='Set eval method.') +parser.add_argument("--source_id_folder", type=str, default='', + help="source_eos_ids folder path.") +parser.add_argument("--target_id_folder", type=str, default='', + help="target_eos_ids folder path.") +parser.add_argument("--result_dir", type=str, default='./result_Files', + help="result dir path.") +args, _ = parser.parse_known_args() + +def read_from_file(config): + ''' + calculate accuraty. + ''' + predictions = [] + probs = [] + source_sentences = [] + target_sentences = [] + file_num = len(os.listdir(args.source_id_folder)) + for i in range(file_num): + f_name = "gigaword_bs_" + str(config.batch_size) + "_" + str(i) + source_ids = np.fromfile(os.path.join(args.source_id_folder, f_name + ".bin"), np.int32) + source_ids = source_ids.reshape(1, config.max_decode_length) + target_ids = np.fromfile(os.path.join(args.target_id_folder, f_name + ".bin"), np.int32) + target_ids = target_ids.reshape(1, config.max_decode_length) + predicted_ids = np.fromfile(os.path.join(args.result_dir, f_name + "_0.bin"), np.int32) + predicted_ids = predicted_ids.reshape(1, config.max_decode_length + 1) + entire_probs = np.fromfile(os.path.join(args.result_dir, f_name + "_1.bin"), np.float32) + entire_probs = entire_probs.reshape(1, config.beam_width, config.max_decode_length + 1) + + source_sentences.append(source_ids) + target_sentences.append(target_ids) + predictions.append(predicted_ids) + probs.append(entire_probs) + + output = [] + for inputs, ref, batch_out, batch_probs in zip(source_sentences, + target_sentences, + predictions, + probs): + for i in range(config.batch_size): + if batch_out.ndim == 3: + batch_out = batch_out[:, 0] + + example = { + "source": inputs[i].tolist(), + "target": ref[i].tolist(), + "prediction": batch_out[i].tolist(), + "prediction_prob": batch_probs[i].tolist() + } + output.append(example) + + return output + + +if __name__ == '__main__': + conf = TransformerConfig.from_json_file(args.config) + result = read_from_file(conf) + vocab = Dictionary.load_from_persisted_dict(args.vocab) + + with open(args.output, "wb") as f: + pickle.dump(result, f, 1) + + # get score by given metric + score = get_score(result, vocab, metric=args.metric) + print(score) diff --git a/model_zoo/official/nlp/mass/preprocess.py b/model_zoo/official/nlp/mass/preprocess.py new file mode 100644 index 00000000000..0a4919d3c75 --- /dev/null +++ b/model_zoo/official/nlp/mass/preprocess.py @@ -0,0 +1,63 @@ +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================ +"""Evaluation api.""" +import os +import argparse +from config import TransformerConfig +from src.dataset import load_dataset + +parser = argparse.ArgumentParser(description='preprocess.') +parser.add_argument("--config", type=str, required=True, + help="Model config json file path.") +parser.add_argument("--result_path", type=str, default='./preprocess_Result/', + help="preprocess result path.") +args, _ = parser.parse_known_args() + +def generate_bin(): + ''' + Generate bin files. + ''' + config = TransformerConfig.from_json_file(args.config) + ds = load_dataset(data_files=config.test_dataset, + batch_size=config.batch_size, + epoch_count=1, + sink_mode=config.dataset_sink_mode, + shuffle=False) if config.test_dataset else None + cur_dir = args.result_path + source_eos_ids_path = os.path.join(cur_dir, "00_source_eos_ids") + source_eos_mask_path = os.path.join(cur_dir, "01_source_eos_mask") + target_eos_ids_path = os.path.join(cur_dir, " target_eos_ids") + + if not os.path.isdir(source_eos_ids_path): + os.makedirs(source_eos_ids_path) + if not os.path.isdir(source_eos_mask_path): + os.makedirs(source_eos_mask_path) + if not os.path.isdir(target_eos_ids_path): + os.makedirs(target_eos_ids_path) + for i, data in enumerate(ds.create_dict_iterator(output_numpy=True, num_epochs=1)): + file_name = "gigaword_bs_" + str(config.batch_size) + "_" + str(i) + ".bin" + source_eos_ids = data['source_eos_ids'] + source_eos_ids.tofile(os.path.join(source_eos_ids_path, file_name)) + + source_eos_mask = data['source_eos_mask'] + source_eos_mask.tofile(os.path.join(source_eos_mask_path, file_name)) + + target_eos_ids = data['target_eos_ids'] + target_eos_ids.tofile(os.path.join(target_eos_ids_path, file_name)) + + print("="*20, "export bin files finished", "="*20) + +if __name__ == '__main__': + generate_bin() diff --git a/model_zoo/official/nlp/mass/scripts/run_infer_310.sh b/model_zoo/official/nlp/mass/scripts/run_infer_310.sh new file mode 100644 index 00000000000..1d7b4d1afc3 --- /dev/null +++ b/model_zoo/official/nlp/mass/scripts/run_infer_310.sh @@ -0,0 +1,126 @@ +#!/bin/bash +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================ + +if [[ $# -lt 5 || $# -gt 6 ]]; then + echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [CONFIG] [VOCAB] [OUTPUT] [NEED_PREPROCESS] [DEVICE_ID] + NEED_PREPROCESS means weather need preprocess or not, it's value is 'y' or 'n'. + DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero" +exit 1 +fi + +get_real_path(){ + if [ "${1:0:1}" == "/" ]; then + echo "$1" + else + echo "$(realpath -m $PWD/$1)" + fi +} +model=$(get_real_path $1) +config=$(get_real_path $2) +vocab=$(get_real_path $3) +output=$(get_real_path $4) + +if [ "$5" == "y" ] || [ "$5" == "n" ];then + need_preprocess=$5 +else + echo "weather need preprocess or not, it's value must be in [y, n]" + exit 1 +fi + +device_id=0 +if [ $# == 6 ]; then + device_id=$6 +fi + +echo "mindir name: "$model +echo "config: "$config +echo "vocab: "$vocab +echo "output: "$output +echo "need preprocess: "$need_preprocess +echo "device id: "$device_id + +export ASCEND_HOME=/usr/local/Ascend/ +if [ -d ${ASCEND_HOME}/ascend-toolkit ]; then + export PATH=$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/atc/bin:$PATH + export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/ascend-toolkit/latest/atc/lib64:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH + export TBE_IMPL_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe + export PYTHONPATH=${TBE_IMPL_PATH}:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/python/site-packages:$PYTHONPATH + export ASCEND_OPP_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp +else + export PATH=$ASCEND_HOME/atc/ccec_compiler/bin:$ASCEND_HOME/atc/bin:$PATH + export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/atc/lib64:$ASCEND_HOME/acllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH + export PYTHONPATH=$ASCEND_HOME/atc/python/site-packages:$PYTHONPATH + export ASCEND_OPP_PATH=$ASCEND_HOME/opp +fi + +function preprocess_data() +{ + if [ -d preprocess_Result ]; then + rm -rf ./preprocess_Result + fi + mkdir preprocess_Result + python3.7 ../preprocess.py --config=$config --result_path=./preprocess_Result/ +} + +function compile_app() +{ + cd ../ascend310_infer || exit + bash build.sh &> build.log +} + +function infer() +{ + cd - || exit + if [ -d result_Files ]; then + rm -rf ./result_Files + fi + if [ -d time_Result ]; then + rm -rf ./time_Result + fi + mkdir result_Files + mkdir time_Result + + ../ascend310_infer/out/main --mindir_path=$model --input0_path=./preprocess_Result/00_source_eos_ids --input1_path=./preprocess_Result/01_source_eos_mask --device_id=$device_id &> infer.log + +} + +function cal_acc() +{ + python3.7 ../postprocess.py --config=$config --vocab=$vocab --output=$output --source_id_folder=./preprocess_Result/00_source_eos_ids --target_id_folder=./preprocess_Result/01_source_eos_mask --result_dir=./result_Files &> acc.log +} + +if [ $need_preprocess == "y" ]; then + preprocess_data + if [ $? -ne 0 ]; then + echo "preprocess dataset failed" + exit 1 + fi +fi +compile_app +if [ $? -ne 0 ]; then + echo "compile app code failed" + exit 1 +fi +infer +if [ $? -ne 0 ]; then + echo " execute inference failed" + exit 1 +fi +cal_acc +if [ $? -ne 0 ]; then + echo "calculate accuracy failed" + exit 1 +fi \ No newline at end of file diff --git a/model_zoo/official/nlp/transformer/README.md b/model_zoo/official/nlp/transformer/README.md index ef42d8778b8..d5cc52cbe9f 100644 --- a/model_zoo/official/nlp/transformer/README.md +++ b/model_zoo/official/nlp/transformer/README.md @@ -13,6 +13,10 @@ - [Dataset Preparation](#dataset-preparation) - [Training Process](#training-process) - [Evaluation Process](#evaluation-process) + - [Inference Process](#inference-process) + - [Export MindIR](#export-mindir) + - [Infer on Ascend310](#infer-on-ascend310) + - [result](#result) - [Model Description](#model-description) - [Performance](#performance) - [Training Performance](#training-performance) @@ -232,6 +236,33 @@ Parameters for learning rate: perl multi-bleu.perl REF_DATA.forbleu < EVAL_OUTPUT.forbleu ``` +## Inference Process + +### [Export MindIR](#contents) + +```shell +python export.py --ckpt_file [CKPT_PATH] --file_name [FILE_NAME] --file_format [FILE_FORMAT] +``` + +The ckpt_file parameter is required, +`EXPORT_FORMAT` should be in ["AIR", "MINDIR"] + +### Infer on Ascend310 + +Before performing inference, the mindir file must be exported by `export.py` script. We only provide an example of inference using MINDIR model. + +```shell +# Ascend310 inference +bash run_infer_310.sh [MINDIR_PATH] [NEED_PREPROCESS] [DEVICE_ID] +``` + +- `NEED_PREPROCESS` means weather need preprocess or not, it's value is 'y' or 'n'. +- `DEVICE_ID` is optional, default value is 0. + +### result + +Inference result is saved in current path, 'output_file' will generate in path specified, For details about how to get BLEU score, see [Evaluation Process](#evaluation-process). + ## [Model Description](#contents) ### [Performance](#contents) diff --git a/model_zoo/official/nlp/transformer/README_CN.md b/model_zoo/official/nlp/transformer/README_CN.md index 54504b2534d..f01e98593ec 100644 --- a/model_zoo/official/nlp/transformer/README_CN.md +++ b/model_zoo/official/nlp/transformer/README_CN.md @@ -19,6 +19,10 @@ - [准备数据集](#准备数据集) - [训练过程](#训练过程) - [评估过程](#评估过程) + - [推理过程](#推理过程) + - [导出MindIR](#导出mindir) + - [在Ascend310执行推理](#在ascend310执行推理) + - [结果](#结果) - [模型描述](#模型描述) - [性能](#性能) - [训练性能](#训练性能) @@ -239,6 +243,33 @@ Parameters for learning rate: perl multi-bleu.perl REF_DATA.forbleu < EVAL_OUTPUT.forbleu ``` +## 推理过程 + +### [导出MindIR](#contents) + +```shell +python export.py --ckpt_file [CKPT_PATH] --file_name [FILE_NAME] --file_format [FILE_FORMAT] +``` + +参数ckpt_file为必填项， +`EXPORT_FORMAT` 必须在 ["AIR", "MINDIR"]中选择。 + +### 在Ascend310执行推理 + +在执行推理前，mindir文件必须通过`export.py`脚本导出。以下展示了使用minir模型执行推理的示例。 + +```shell +# Ascend310 推理 +bash run_infer_310.sh [MINDIR_PATH] [NEED_PREPROCESS] [DEVICE_ID] +``` + +- `NEED_PREPROCESS` 表示是否需要对数据集进行预处理, 取值为'y' 或者 'n'。 +- `DEVICE_ID` 可选，默认值为0。 + +### 结果 + +推理结果保存在脚本执行的当前路径，'output_file' 将会生成在指定路径，生成BLEU分数的过程请参照[评估过程](#评估过程). + ## 模型描述 ### 性能 diff --git a/model_zoo/official/nlp/transformer/ascend310_infer/CMakeLists.txt b/model_zoo/official/nlp/transformer/ascend310_infer/CMakeLists.txt new file mode 100644 index 00000000000..ee3c8544734 --- /dev/null +++ b/model_zoo/official/nlp/transformer/ascend310_infer/CMakeLists.txt @@ -0,0 +1,14 @@ +cmake_minimum_required(VERSION 3.14.1) +project(Ascend310Infer) +add_compile_definitions(_GLIBCXX_USE_CXX11_ABI=0) +set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O0 -g -std=c++17 -Werror -Wall -fPIE -Wl,--allow-shlib-undefined") +set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/) +option(MINDSPORE_PATH "mindspore install path" "") +include_directories(${MINDSPORE_PATH}) +include_directories(${MINDSPORE_PATH}/include) +include_directories(${PROJECT_SRC_ROOT}) +find_library(MS_LIB libmindspore.so ${MINDSPORE_PATH}/lib) +file(GLOB_RECURSE MD_LIB ${MINDSPORE_PATH}/_c_dataengine*) + +add_executable(main src/main.cc src/utils.cc) +target_link_libraries(main ${MS_LIB} ${MD_LIB} gflags) diff --git a/model_zoo/official/nlp/transformer/ascend310_infer/build.sh b/model_zoo/official/nlp/transformer/ascend310_infer/build.sh new file mode 100644 index 00000000000..285514e19f2 --- /dev/null +++ b/model_zoo/official/nlp/transformer/ascend310_infer/build.sh @@ -0,0 +1,29 @@ +#!/bin/bash +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================ +if [ -d out ]; then + rm -rf out +fi + +mkdir out +cd out || exit + +if [ -f "Makefile" ]; then + make clean +fi + +cmake .. \ + -DMINDSPORE_PATH="`pip3.7 show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`" +make diff --git a/model_zoo/official/nlp/transformer/ascend310_infer/inc/utils.h b/model_zoo/official/nlp/transformer/ascend310_infer/inc/utils.h new file mode 100644 index 00000000000..efebe03a8c1 --- /dev/null +++ b/model_zoo/official/nlp/transformer/ascend310_infer/inc/utils.h @@ -0,0 +1,32 @@ +/** + * Copyright 2021 Huawei Technologies Co., Ltd + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#ifndef MINDSPORE_INFERENCE_UTILS_H_ +#define MINDSPORE_INFERENCE_UTILS_H_ + +#include +#include +#include +#include +#include +#include "include/api/types.h" + +std::vector GetAllFiles(std::string_view dirName); +DIR *OpenDir(std::string_view dirName); +std::string RealPath(std::string_view path); +mindspore::MSTensor ReadFileToTensor(const std::string &file); +int WriteResult(const std::string& imageFile, const std::vector &outputs); +#endif diff --git a/model_zoo/official/nlp/transformer/ascend310_infer/src/main.cc b/model_zoo/official/nlp/transformer/ascend310_infer/src/main.cc new file mode 100644 index 00000000000..61b08344f97 --- /dev/null +++ b/model_zoo/official/nlp/transformer/ascend310_infer/src/main.cc @@ -0,0 +1,137 @@ +/** + * Copyright 2021 Huawei Technologies Co., Ltd + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include "include/api/model.h" +#include "include/api/context.h" +#include "include/api/types.h" +#include "include/api/serialization.h" +#include "include/dataset/execute.h" +#include "include/dataset/vision.h" +#include "inc/utils.h" + +using mindspore::Context; +using mindspore::Serialization; +using mindspore::Model; +using mindspore::Status; +using mindspore::MSTensor; +using mindspore::dataset::Execute; +using mindspore::ModelType; +using mindspore::GraphCell; +using mindspore::kSuccess; + +DEFINE_string(mindir_path, "", "mindir path"); +DEFINE_string(input0_path, ".", "input0 path"); +DEFINE_string(input1_path, ".", "input1 path"); +DEFINE_int32(device_id, 0, "device id"); + +int main(int argc, char **argv) { + gflags::ParseCommandLineFlags(&argc, &argv, true); + if (RealPath(FLAGS_mindir_path).empty()) { + std::cout << "Invalid mindir" << std::endl; + return 1; + } + + auto context = std::make_shared(); + auto ascend310 = std::make_shared(); + ascend310->SetDeviceID(FLAGS_device_id); + ascend310->SetPrecisionMode("allow_fp32_to_fp16"); + ascend310->SetOpSelectImplMode("high_precision"); + context->MutableDeviceInfo().push_back(ascend310); + mindspore::Graph graph; + Serialization::Load(FLAGS_mindir_path, ModelType::kMindIR, &graph); + + Model model; + Status ret = model.Build(GraphCell(graph), context); + if (ret != kSuccess) { + std::cout << "ERROR: Build failed." << std::endl; + return 1; + } + + std::vector model_inputs = model.GetInputs(); + if (model_inputs.empty()) { + std::cout << "Invalid model, inputs is empty." << std::endl; + return 1; + } + + auto input0_files = GetAllFiles(FLAGS_input0_path); + auto input1_files = GetAllFiles(FLAGS_input1_path); + + if (input0_files.empty() || input1_files.empty()) { + std::cout << "ERROR: input data empty." << std::endl; + return 1; + } + + std::map costTime_map; + size_t size = input0_files.size(); + + for (size_t i = 0; i < size; ++i) { + struct timeval start = {0}; + struct timeval end = {0}; + double startTimeMs; + double endTimeMs; + std::vector inputs; + std::vector outputs; + std::cout << "Start predict input files:" << input0_files[i] << std::endl; + + auto input0 = ReadFileToTensor(input0_files[i]); + auto input1 = ReadFileToTensor(input1_files[i]); + inputs.emplace_back(model_inputs[0].Name(), model_inputs[0].DataType(), model_inputs[0].Shape(), + input0.Data().get(), input0.DataSize()); + inputs.emplace_back(model_inputs[1].Name(), model_inputs[1].DataType(), model_inputs[1].Shape(), + input1.Data().get(), input1.DataSize()); + + gettimeofday(&start, nullptr); + ret = model.Predict(inputs, &outputs); + gettimeofday(&end, nullptr); + if (ret != kSuccess) { + std::cout << "Predict " << input0_files[i] << " failed." << std::endl; + return 1; + } + startTimeMs = (1.0 * start.tv_sec * 1000000 + start.tv_usec) / 1000; + endTimeMs = (1.0 * end.tv_sec * 1000000 + end.tv_usec) / 1000; + costTime_map.insert(std::pair(startTimeMs, endTimeMs)); + WriteResult(input0_files[i], outputs); + } + double average = 0.0; + int inferCount = 0; + + for (auto iter = costTime_map.begin(); iter != costTime_map.end(); iter++) { + double diff = 0.0; + diff = iter->second - iter->first; + average += diff; + inferCount++; + } + average = average / inferCount; + std::stringstream timeCost; + timeCost << "NN inference cost average time: "<< average << " ms of infer_count " << inferCount << std::endl; + std::cout << "NN inference cost average time: "<< average << "ms of infer_count " << inferCount << std::endl; + std::string fileName = "./time_Result" + std::string("/test_perform_static.txt"); + std::ofstream fileStream(fileName.c_str(), std::ios::trunc); + fileStream << timeCost.str(); + fileStream.close(); + costTime_map.clear(); + return 0; +} diff --git a/model_zoo/official/nlp/transformer/ascend310_infer/src/utils.cc b/model_zoo/official/nlp/transformer/ascend310_infer/src/utils.cc new file mode 100644 index 00000000000..c947e4d5f45 --- /dev/null +++ b/model_zoo/official/nlp/transformer/ascend310_infer/src/utils.cc @@ -0,0 +1,129 @@ +/** + * Copyright 2021 Huawei Technologies Co., Ltd + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#include +#include +#include +#include "inc/utils.h" + +using mindspore::MSTensor; +using mindspore::DataType; + +std::vector GetAllFiles(std::string_view dirName) { + struct dirent *filename; + DIR *dir = OpenDir(dirName); + if (dir == nullptr) { + return {}; + } + std::vector res; + while ((filename = readdir(dir)) != nullptr) { + std::string dName = std::string(filename->d_name); + if (dName == "." || dName == ".." || filename->d_type != DT_REG) { + continue; + } + res.emplace_back(std::string(dirName) + "/" + filename->d_name); + } + std::sort(res.begin(), res.end()); + for (auto &f : res) { + std::cout << "image file: " << f << std::endl; + } + return res; +} + +int WriteResult(const std::string& imageFile, const std::vector &outputs) { + std::string homePath = "./result_Files"; + for (size_t i = 0; i < outputs.size(); ++i) { + size_t outputSize; + std::shared_ptr netOutput; + netOutput = outputs[i].Data(); + outputSize = outputs[i].DataSize(); + int pos = imageFile.rfind('/'); + std::string fileName(imageFile, pos + 1); + fileName.replace(fileName.find('.'), fileName.size() - fileName.find('.'), '_' + std::to_string(i) + ".bin"); + std::string outFileName = homePath + "/" + fileName; + FILE * outputFile = fopen(outFileName.c_str(), "wb"); + fwrite(netOutput.get(), outputSize, sizeof(char), outputFile); + fclose(outputFile); + outputFile = nullptr; + } + return 0; +} + +mindspore::MSTensor ReadFileToTensor(const std::string &file) { + if (file.empty()) { + std::cout << "Pointer file is nullptr" << std::endl; + return mindspore::MSTensor(); + } + + std::ifstream ifs(file); + if (!ifs.good()) { + std::cout << "File: " << file << " is not exist" << std::endl; + return mindspore::MSTensor(); + } + + if (!ifs.is_open()) { + std::cout << "File: " << file << "open failed" << std::endl; + return mindspore::MSTensor(); + } + + ifs.seekg(0, std::ios::end); + size_t size = ifs.tellg(); + mindspore::MSTensor buffer(file, mindspore::DataType::kNumberTypeUInt8, {static_cast(size)}, nullptr, size); + + ifs.seekg(0, std::ios::beg); + ifs.read(reinterpret_cast(buffer.MutableData()), size); + ifs.close(); + + return buffer; +} + + +DIR *OpenDir(std::string_view dirName) { + if (dirName.empty()) { + std::cout << " dirName is null ! " << std::endl; + return nullptr; + } + std::string realPath = RealPath(dirName); + struct stat s; + lstat(realPath.c_str(), &s); + if (!S_ISDIR(s.st_mode)) { + std::cout << "dirName is not a valid directory !" << std::endl; + return nullptr; + } + DIR *dir; + dir = opendir(realPath.c_str()); + if (dir == nullptr) { + std::cout << "Can not open dir " << dirName << std::endl; + return nullptr; + } + std::cout << "Successfully opened the dir " << dirName << std::endl; + return dir; +} + +std::string RealPath(std::string_view path) { + char realPathMem[PATH_MAX] = {0}; + char *realPathRet = nullptr; + realPathRet = realpath(path.data(), realPathMem); + + if (realPathRet == nullptr) { + std::cout << "File: " << path << " is not exist."; + return ""; + } + + std::string realPath(realPathMem); + std::cout << path << " realpath is: " << realPath << std::endl; + return realPath; +} diff --git a/model_zoo/official/nlp/transformer/postprocess.py b/model_zoo/official/nlp/transformer/postprocess.py new file mode 100644 index 00000000000..93c5f95ceb4 --- /dev/null +++ b/model_zoo/official/nlp/transformer/postprocess.py @@ -0,0 +1,51 @@ +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================ +"""Transformer evaluation script.""" + +import os +import argparse +import numpy as np + +from src.eval_config import cfg, transformer_net_cfg + +parser = argparse.ArgumentParser(description='postprocess') +parser.add_argument("--result_dir", type=str, default="./result_Files", + help="infer result path.") +args = parser.parse_args() + +def generate_output(): + ''' + Generate output. + ''' + predictions = [] + file_num = len(os.listdir(args.result_dir)) + for i in range(file_num): + batch = "transformer_bs_" + str(transformer_net_cfg.batch_size) + "_" + str(i) + "_0.bin" + pred = np.fromfile(os.path.join(args.result_dir, batch), np.int32) + predictions.append(pred.reshape(1, 1, transformer_net_cfg.max_decode_length + 1)) + + # decode and write to file + f = open(cfg.output_file, 'w') + for batch_out in predictions: + for i in range(transformer_net_cfg.batch_size): + if batch_out.ndim == 3: + batch_out = batch_out[:, 0] + token_ids = [str(x) for x in batch_out[i].tolist()] + f.write(" ".join(token_ids) + "\n") + f.close() + + +if __name__ == "__main__": + generate_output() diff --git a/model_zoo/official/nlp/transformer/preprocess.py b/model_zoo/official/nlp/transformer/preprocess.py new file mode 100644 index 00000000000..ba163e943cc --- /dev/null +++ b/model_zoo/official/nlp/transformer/preprocess.py @@ -0,0 +1,58 @@ +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================ +"""Transformer evaluation script.""" + +import os +import argparse + +from src.eval_config import cfg, transformer_net_cfg +from eval import load_test_data + +parser = argparse.ArgumentParser(description='preprocess') +parser.add_argument("--result_path", type=str, default="./preprocess_Result/", + help="preprocess result path.") +args = parser.parse_args() + + +def generate_bin(): + ''' + Generate bin files. + ''' + dataset = load_test_data(batch_size=transformer_net_cfg.batch_size, data_file=cfg.data_file) + cur_dir = args.result_path + + source_eos_ids_path = os.path.join(cur_dir, "00_source_eos_ids") + source_eos_mask_path = os.path.join(cur_dir, "01_source_eos_mask") + + if not os.path.isdir(source_eos_ids_path): + os.makedirs(source_eos_ids_path) + if not os.path.isdir(source_eos_mask_path): + os.makedirs(source_eos_mask_path) + + batch_size = transformer_net_cfg.batch_size + + for i, data in enumerate(dataset.create_dict_iterator(output_numpy=True, num_epochs=1)): + file_name = "transformer_bs_" + str(batch_size) + "_" + str(i) + ".bin" + source_eos_ids = data['source_eos_ids'] + source_eos_ids.tofile(os.path.join(source_eos_ids_path, file_name)) + + source_eos_mask = data['source_eos_mask'] + source_eos_mask.tofile(os.path.join(source_eos_mask_path, file_name)) + + print("="*20, "export bin files finished", "="*20) + + +if __name__ == "__main__": + generate_bin() diff --git a/model_zoo/official/nlp/transformer/scripts/run_infer_310.sh b/model_zoo/official/nlp/transformer/scripts/run_infer_310.sh new file mode 100644 index 00000000000..cd7e57b7080 --- /dev/null +++ b/model_zoo/official/nlp/transformer/scripts/run_infer_310.sh @@ -0,0 +1,120 @@ +#!/bin/bash +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================ + +if [[ $# -lt 2 || $# -gt 3 ]]; then + echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [NEED_PREPROCESS] [DEVICE_ID] + NEED_PREPROCESS means weather need preprocess or not, it's value is 'y' or 'n'. + DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero" +exit 1 +fi + +get_real_path(){ + if [ "${1:0:1}" == "/" ]; then + echo "$1" + else + echo "$(realpath -m $PWD/$1)" + fi +} +model=$(get_real_path $1) + +if [ "$2" == "y" ] || [ "$2" == "n" ];then + need_preprocess=$2 +else + echo "weather need preprocess or not, it's value must be in [y, n]" + exit 1 +fi + +device_id=0 +if [ $# == 3 ]; then + device_id=$3 +fi + +echo "mindir name: "$model +echo "need preprocess: "$need_preprocess +echo "device id: "$device_id + +export ASCEND_HOME=/usr/local/Ascend/ +if [ -d ${ASCEND_HOME}/ascend-toolkit ]; then + export PATH=$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/atc/bin:$PATH + export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/ascend-toolkit/latest/atc/lib64:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH + export TBE_IMPL_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe + export PYTHONPATH=${TBE_IMPL_PATH}:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/python/site-packages:$PYTHONPATH + export ASCEND_OPP_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp +else + export PATH=$ASCEND_HOME/atc/ccec_compiler/bin:$ASCEND_HOME/atc/bin:$PATH + export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/atc/lib64:$ASCEND_HOME/acllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH + export PYTHONPATH=$ASCEND_HOME/atc/python/site-packages:$PYTHONPATH + export ASCEND_OPP_PATH=$ASCEND_HOME/opp +fi + +function preprocess_data() +{ + if [ -d preprocess_Result ]; then + rm -rf ./preprocess_Result + fi + mkdir preprocess_Result + python3.7 ../preprocess.py --result_path=./preprocess_Result/ +} + +function compile_app() +{ + cd ../ascend310_infer || exit + bash build.sh &> build.log +} + +function infer() +{ + cd - || exit + if [ -d result_Files ]; then + rm -rf ./result_Files + fi + if [ -d time_Result ]; then + rm -rf ./time_Result + fi + mkdir result_Files + mkdir time_Result + + ../ascend310_infer/out/main --mindir_path=$model --input0_path=./preprocess_Result/00_source_eos_ids --input1_path=./preprocess_Result/01_source_eos_mask --device_id=$device_id &> infer.log + +} + +function cal_acc() +{ + python3.7 ../postprocess.py --result_dir=./result_Files &> acc.log +} + +if [ $need_preprocess == "y" ]; then + preprocess_data + if [ $? -ne 0 ]; then + echo "preprocess dataset failed" + exit 1 + fi +fi +compile_app +if [ $? -ne 0 ]; then + echo "compile app code failed" + exit 1 +fi +infer +if [ $? -ne 0 ]; then + echo " execute inference failed" + exit 1 +fi +cal_acc +if [ $? -ne 0 ]; then + echo "calculate accuracy failed" + exit 1 +fi \ No newline at end of file diff --git a/model_zoo/research/cv/advanced_east/README.md b/model_zoo/research/cv/advanced_east/README.md index 04ae4fc545f..ad41900bb77 100644 --- a/model_zoo/research/cv/advanced_east/README.md +++ b/model_zoo/research/cv/advanced_east/README.md @@ -161,6 +161,34 @@ config.py： The above python command will run in the background, you can view the results through the file output.eval.log. You will get the accuracy as following: +## Inference Process + +### [Export MindIR](#contents) + +```shell +python export.py --ckpt_file [CKPT_PATH] --file_name [FILE_NAME] --file_format [FILE_FORMAT] +``` + +The ckpt_file parameter is required, +`EXPORT_FORMAT` should be in ["AIR", "MINDIR"] + +### Infer on Ascend310 + +Before performing inference, the mindir file must be exported by `export.py` script. We only provide an example of inference using MINDIR model. +Current batch_size can only be set to 1. + +```shell +# Ascend310 inference +bash run_infer_310.sh [MINDIR_PATH] [NEED_PREPROCESS] [DEVICE_ID] +``` + +`NEED_PREPROCESS` means weather need preprocess or not, it's value is 'y' or 'n'. +`DEVICE_ID` is optional, default value is 0. + +### result + +Inference result is saved in current path, you can find result in acc.log file. + ## performance ### Training performance diff --git a/model_zoo/research/cv/advanced_east/ascend310_infer/CMakeLists.txt b/model_zoo/research/cv/advanced_east/ascend310_infer/CMakeLists.txt new file mode 100644 index 00000000000..ee3c8544734 --- /dev/null +++ b/model_zoo/research/cv/advanced_east/ascend310_infer/CMakeLists.txt @@ -0,0 +1,14 @@ +cmake_minimum_required(VERSION 3.14.1) +project(Ascend310Infer) +add_compile_definitions(_GLIBCXX_USE_CXX11_ABI=0) +set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O0 -g -std=c++17 -Werror -Wall -fPIE -Wl,--allow-shlib-undefined") +set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/) +option(MINDSPORE_PATH "mindspore install path" "") +include_directories(${MINDSPORE_PATH}) +include_directories(${MINDSPORE_PATH}/include) +include_directories(${PROJECT_SRC_ROOT}) +find_library(MS_LIB libmindspore.so ${MINDSPORE_PATH}/lib) +file(GLOB_RECURSE MD_LIB ${MINDSPORE_PATH}/_c_dataengine*) + +add_executable(main src/main.cc src/utils.cc) +target_link_libraries(main ${MS_LIB} ${MD_LIB} gflags) diff --git a/model_zoo/research/cv/advanced_east/ascend310_infer/build.sh b/model_zoo/research/cv/advanced_east/ascend310_infer/build.sh new file mode 100644 index 00000000000..285514e19f2 --- /dev/null +++ b/model_zoo/research/cv/advanced_east/ascend310_infer/build.sh @@ -0,0 +1,29 @@ +#!/bin/bash +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================ +if [ -d out ]; then + rm -rf out +fi + +mkdir out +cd out || exit + +if [ -f "Makefile" ]; then + make clean +fi + +cmake .. \ + -DMINDSPORE_PATH="`pip3.7 show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`" +make diff --git a/model_zoo/research/cv/advanced_east/ascend310_infer/inc/utils.h b/model_zoo/research/cv/advanced_east/ascend310_infer/inc/utils.h new file mode 100644 index 00000000000..f8ae1e5b473 --- /dev/null +++ b/model_zoo/research/cv/advanced_east/ascend310_infer/inc/utils.h @@ -0,0 +1,35 @@ +/** + * Copyright 2021 Huawei Technologies Co., Ltd + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#ifndef MINDSPORE_INFERENCE_UTILS_H_ +#define MINDSPORE_INFERENCE_UTILS_H_ + +#include +#include +#include +#include +#include +#include "include/api/types.h" + +std::vector GetAllFiles(std::string_view dirName); +DIR *OpenDir(std::string_view dirName); +std::string RealPath(std::string_view path); +mindspore::MSTensor ReadFileToTensor(const std::string &file); +int WriteResult(const std::string& imageFile, const std::vector &outputs); +std::vector GetAllFiles(std::string dir_name); +std::vector> GetAllInputData(std::string dir_name); + +#endif diff --git a/model_zoo/research/cv/advanced_east/ascend310_infer/src/main.cc b/model_zoo/research/cv/advanced_east/ascend310_infer/src/main.cc new file mode 100644 index 00000000000..cd9767a77e3 --- /dev/null +++ b/model_zoo/research/cv/advanced_east/ascend310_infer/src/main.cc @@ -0,0 +1,144 @@ +/** + * Copyright 2021 Huawei Technologies Co., Ltd + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include "include/api/model.h" +#include "include/api/serialization.h" +#include "include/api/context.h" +#include "include/dataset/execute.h" +#include "include/dataset/vision.h" +#include "include/dataset/config.h" +#include "../inc/utils.h" +#include "include/api/types.h" + + +using mindspore::Context; +using mindspore::Serialization; +using mindspore::Model; +using mindspore::Status; +using mindspore::dataset::Execute; +using mindspore::MSTensor; +using mindspore::ModelType; +using mindspore::GraphCell; +using mindspore::kSuccess; + +using mindspore::dataset::vision::Decode; +using mindspore::dataset::vision::Normalize; +using mindspore::dataset::vision::Resize; +using mindspore::dataset::vision::HWC2CHW; +using mindspore::dataset::InterpolationMode; + +DEFINE_string(mindir_path, "", "mindir path"); +DEFINE_string(dataset_path, ".", "dataset path"); +DEFINE_int32(device_id, 0, "device id"); + +int main(int argc, char **argv) { + gflags::ParseCommandLineFlags(&argc, &argv, true); + if (RealPath(FLAGS_mindir_path).empty()) { + std::cout << "Invalid mindir" << std::endl; + return 1; + } + + auto context = std::make_shared(); + auto ascend310 = std::make_shared(); + ascend310->SetDeviceID(FLAGS_device_id); + ascend310->SetPrecisionMode("allow_fp32_to_fp16"); + context->MutableDeviceInfo().push_back(ascend310); + + mindspore::Graph graph; + Serialization::Load(FLAGS_mindir_path, ModelType::kMindIR, &graph); + Model model; + Status ret = model.Build(GraphCell(graph), context); + if (ret != kSuccess) { + std::cout << "ERROR: Build failed." << std::endl; + return 1; + } + + std::vector model_inputs = model.GetInputs(); + auto all_files = GetAllFiles(FLAGS_dataset_path); + if (all_files.empty()) { + std::cout << "ERROR: no input data." << std::endl; + return 1; + } + + std::map costTime_map; + size_t size = all_files.size(); + + auto decode(new Decode()); + auto resize(new Resize({448, 448}, InterpolationMode::kNearestNeighbour)); + auto normalize(new Normalize({123.68, 116.779, 103.939}, {1.0, 1.0, 1.0})); + auto hwc2chw(new HWC2CHW()); + Execute preprocess({decode, resize, normalize, hwc2chw}); + + for (size_t i = 0; i < size; ++i) { + struct timeval start = {0}; + struct timeval end = {0}; + double startTimeMs; + double endTimeMs; + std::vector inputs; + std::vector outputs; + std::cout << "Start predict input files:" << all_files[i] <(startTimeMs, endTimeMs)); + WriteResult(all_files[i], outputs); + } + double average = 0.0; + int inferCount = 0; + + for (auto iter = costTime_map.begin(); iter != costTime_map.end(); iter++) { + double diff = 0.0; + diff = iter->second - iter->first; + average += diff; + inferCount++; + } + average = average / inferCount; + std::stringstream timeCost; + timeCost << "NN inference cost average time: "<< average << " ms of infer_count " << inferCount << std::endl; + std::cout << "NN inference cost average time: "<< average << "ms of infer_count " << inferCount << std::endl; + std::string fileName = "./time_Result" + std::string("/test_perform_static.txt"); + std::ofstream fileStream(fileName.c_str(), std::ios::trunc); + fileStream << timeCost.str(); + fileStream.close(); + costTime_map.clear(); + return 0; +} diff --git a/model_zoo/research/cv/advanced_east/ascend310_infer/src/utils.cc b/model_zoo/research/cv/advanced_east/ascend310_infer/src/utils.cc new file mode 100644 index 00000000000..27dfa015021 --- /dev/null +++ b/model_zoo/research/cv/advanced_east/ascend310_infer/src/utils.cc @@ -0,0 +1,185 @@ +/** + * Copyright 2021 Huawei Technologies Co., Ltd + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#include +#include +#include +#include "inc/utils.h" + +using mindspore::MSTensor; +using mindspore::DataType; + + +std::vector> GetAllInputData(std::string dir_name) { + std::vector> ret; + + DIR *dir = OpenDir(dir_name); + if (dir == nullptr) { + return {}; + } + struct dirent *filename; + /* read all the files in the dir ~ */ + std::vector sub_dirs; + while ((filename = readdir(dir)) != nullptr) { + std::string d_name = std::string(filename->d_name); + // get rid of "." and ".." + if (d_name == "." || d_name == ".." || d_name.empty()) { + continue; + } + std::string dir_path = RealPath(std::string(dir_name) + "/" + filename->d_name); + struct stat s; + lstat(dir_path.c_str(), &s); + if (!S_ISDIR(s.st_mode)) { + continue; + } + + sub_dirs.emplace_back(dir_path); + } + std::sort(sub_dirs.begin(), sub_dirs.end()); + + (void)std::transform(sub_dirs.begin(), sub_dirs.end(), std::back_inserter(ret), + [](const std::string &d) { return GetAllFiles(d); }); + + return ret; +} + + +std::vector GetAllFiles(std::string dir_name) { + struct dirent *filename; + DIR *dir = OpenDir(dir_name); + if (dir == nullptr) { + return {}; + } + + std::vector res; + while ((filename = readdir(dir)) != nullptr) { + std::string d_name = std::string(filename->d_name); + if (d_name == "." || d_name == ".." || d_name.size() <= 3) { + continue; + } + res.emplace_back(std::string(dir_name) + "/" + filename->d_name); + } + std::sort(res.begin(), res.end()); + + return res; +} + + +std::vector GetAllFiles(std::string_view dirName) { + struct dirent *filename; + DIR *dir = OpenDir(dirName); + if (dir == nullptr) { + return {}; + } + std::vector res; + while ((filename = readdir(dir)) != nullptr) { + std::string dName = std::string(filename->d_name); + if (dName == "." || dName == ".." || filename->d_type != DT_REG) { + continue; + } + res.emplace_back(std::string(dirName) + "/" + filename->d_name); + } + std::sort(res.begin(), res.end()); + for (auto &f : res) { + std::cout << "image file: " << f << std::endl; + } + return res; +} + + +int WriteResult(const std::string& imageFile, const std::vector &outputs) { + std::string homePath = "./result_Files"; + for (size_t i = 0; i < outputs.size(); ++i) { + size_t outputSize; + std::shared_ptr netOutput; + netOutput = outputs[i].Data(); + outputSize = outputs[i].DataSize(); + int pos = imageFile.rfind('/'); + std::string fileName(imageFile, pos + 1); + fileName = fileName + '_' + std::to_string(i) + ".bin"; + std::string outFileName = homePath + "/" + fileName; + FILE *outputFile = fopen(outFileName.c_str(), "wb"); + fwrite(netOutput.get(), outputSize, sizeof(char), outputFile); + fclose(outputFile); + outputFile = nullptr; + } + return 0; +} + +mindspore::MSTensor ReadFileToTensor(const std::string &file) { + if (file.empty()) { + std::cout << "Pointer file is nullptr" << std::endl; + return mindspore::MSTensor(); + } + + std::ifstream ifs(file); + if (!ifs.good()) { + std::cout << "File: " << file << " is not exist" << std::endl; + return mindspore::MSTensor(); + } + + if (!ifs.is_open()) { + std::cout << "File: " << file << "open failed" << std::endl; + return mindspore::MSTensor(); + } + + ifs.seekg(0, std::ios::end); + size_t size = ifs.tellg(); + mindspore::MSTensor buffer(file, mindspore::DataType::kNumberTypeUInt8, {static_cast(size)}, nullptr, size); + + ifs.seekg(0, std::ios::beg); + ifs.read(reinterpret_cast(buffer.MutableData()), size); + ifs.close(); + + return buffer; +} + + +DIR *OpenDir(std::string_view dirName) { + if (dirName.empty()) { + std::cout << " dirName is null ! " << std::endl; + return nullptr; + } + std::string realPath = RealPath(dirName); + struct stat s; + lstat(realPath.c_str(), &s); + if (!S_ISDIR(s.st_mode)) { + std::cout << "dirName is not a valid directory !" << std::endl; + return nullptr; + } + DIR *dir; + dir = opendir(realPath.c_str()); + if (dir == nullptr) { + std::cout << "Can not open dir " << dirName << std::endl; + return nullptr; + } + std::cout << "Successfully opened the dir " << dirName << std::endl; + return dir; +} + +std::string RealPath(std::string_view path) { + char realPathMem[PATH_MAX] = {0}; + char *realPathRet = nullptr; + realPathRet = realpath(path.data(), realPathMem); + if (realPathRet == nullptr) { + std::cout << "File: " << path << " is not exist."; + return ""; + } + + std::string realPath(realPathMem); + std::cout << path << " realpath is: " << realPath << std::endl; + return realPath; +} diff --git a/model_zoo/research/cv/advanced_east/postprocess.py b/model_zoo/research/cv/advanced_east/postprocess.py new file mode 100644 index 00000000000..f0797b69bba --- /dev/null +++ b/model_zoo/research/cv/advanced_east/postprocess.py @@ -0,0 +1,60 @@ +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================ +""" +#################postprocess######################## +""" +import os +import argparse +import numpy as np +from mindspore import Tensor +from src.config import config as cfg +from src.score import eval_pre_rec_f1 + + +def parse_args(cloud_args=None): + """parameters""" + parser = argparse.ArgumentParser('postprocess') + parser.add_argument('--rst_path', type=str, default='./result_Files/', + help='infer result path.') + args_opt = parser.parse_args() + + args_opt.data_dir = cfg.data_dir + args_opt.train_image_dir_name = os.path.join(cfg.data_dir, cfg.train_image_dir_name) + args_opt.val_fname = cfg.val_fname + args_opt.train_label_dir_name = os.path.join(cfg.data_dir, cfg.train_label_dir_name) + args_opt.batch_size = 1 + + return args_opt + + +if __name__ == '__main__': + arg = parse_args() + obj = eval_pre_rec_f1() + with open(os.path.join(arg.data_dir, arg.val_fname), 'r') as f_val: + f_list = f_val.readlines() + + batch_list = np.arange(0, len(f_list), arg.batch_size) + for idx in batch_list: + gt_list = [] + for i in range(idx, min(idx + arg.batch_size, len(f_list))): + item = f_list[i] + img_filename = str(item).strip().split(',')[0] + gt_list.append(np.load(os.path.join(arg.train_label_dir_name, img_filename[:-4]) + '.npy')) + y = np.fromfile(os.path.join(arg.rst_path, img_filename + '_0.bin'), np.float32) + y = Tensor(y.reshape(1, 7, 112, 112)) + + obj.add(y, gt_list) + + print(obj.val()) diff --git a/model_zoo/research/cv/advanced_east/preprocess.py b/model_zoo/research/cv/advanced_east/preprocess.py new file mode 100644 index 00000000000..089e420eed4 --- /dev/null +++ b/model_zoo/research/cv/advanced_east/preprocess.py @@ -0,0 +1,50 @@ +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================ +""" +################preprocess######################## +""" +import argparse +import os + +from PIL import Image +from src.config import config as cfg + +def parse_args(cloud_args=None): + """parameters""" + parser = argparse.ArgumentParser('preprocess') + parser.add_argument('--result_path', type=str, default='./preprocess_Result/', + help='result path') + args_opt = parser.parse_args() + + args_opt.data_dir = cfg.data_dir + args_opt.train_image_dir_name = os.path.join(cfg.data_dir, cfg.train_image_dir_name) + args_opt.val_fname = cfg.val_fname + + return args_opt + +def prepare_valset(arg): + """generate validate dataset.""" + with open(os.path.join(arg.data_dir, arg.val_fname), 'r') as f_val: + f_list = f_val.readlines() + for i, _ in enumerate(f_list): + item = f_list[i] + img_filename = str(item).strip().split(',')[0] + img_path = os.path.join(arg.train_image_dir_name, img_filename) + img = Image.open(img_path) + img.save(os.path.join(arg.result_path, img_filename)) + +if __name__ == '__main__': + args = parse_args() + prepare_valset(args) diff --git a/model_zoo/research/cv/advanced_east/scripts/run_infer_310.sh b/model_zoo/research/cv/advanced_east/scripts/run_infer_310.sh new file mode 100644 index 00000000000..10f17bdd379 --- /dev/null +++ b/model_zoo/research/cv/advanced_east/scripts/run_infer_310.sh @@ -0,0 +1,120 @@ +#!/bin/bash +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================ + +if [[ $# -lt 2 || $# -gt 3 ]]; then + echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [NEED_PREPROCESS] [DEVICE_ID] + NEED_PREPROCESS means weather need preprocess or not, it's value is 'y' or 'n'. + DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero" +exit 1 +fi + +get_real_path(){ + if [ "${1:0:1}" == "/" ]; then + echo "$1" + else + echo "$(realpath -m $PWD/$1)" + fi +} +model=$(get_real_path $1) + +if [ "$2" == "y" ] || [ "$2" == "n" ];then + need_preprocess=$2 +else + echo "weather need preprocess or not, it's value must be in [y, n]" + exit 1 +fi + +device_id=0 +if [ $# == 3 ]; then + device_id=$3 +fi + +echo "mindir name: "$model +echo "need preprocess: "$need_preprocess +echo "device id: "$device_id + +export ASCEND_HOME=/usr/local/Ascend/ +if [ -d ${ASCEND_HOME}/ascend-toolkit ]; then + export PATH=$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/atc/bin:$PATH + export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/ascend-toolkit/latest/atc/lib64:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH + export TBE_IMPL_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe + export PYTHONPATH=${TBE_IMPL_PATH}:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/python/site-packages:$PYTHONPATH + export ASCEND_OPP_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp +else + export PATH=$ASCEND_HOME/atc/ccec_compiler/bin:$ASCEND_HOME/atc/bin:$PATH + export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/atc/lib64:$ASCEND_HOME/acllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH + export PYTHONPATH=$ASCEND_HOME/atc/python/site-packages:$PYTHONPATH + export ASCEND_OPP_PATH=$ASCEND_HOME/opp +fi + +function preprocess_data() +{ + if [ -d preprocess_Result ]; then + rm -rf ./preprocess_Result + fi + mkdir preprocess_Result + python3.7 ../preprocess.py --result_path=./preprocess_Result/ +} + +function compile_app() +{ + cd ../ascend310_infer || exit + bash build.sh &> build.log +} + +function infer() +{ + cd - || exit + if [ -d result_Files ]; then + rm -rf ./result_Files + fi + if [ -d time_Result ]; then + rm -rf ./time_Result + fi + mkdir result_Files + mkdir time_Result + + ../ascend310_infer/out/main --mindir_path=$model --dataset_path=./preprocess_Result/ --device_id=$device_id &> infer.log + +} + +function cal_acc() +{ + python3.7 ../postprocess.py --rst_path=./result_Files &> acc.log +} + +if [ $need_preprocess == "y" ]; then + preprocess_data + if [ $? -ne 0 ]; then + echo "preprocess dataset failed" + exit 1 + fi +fi +compile_app +if [ $? -ne 0 ]; then + echo "compile app code failed" + exit 1 +fi +infer +if [ $? -ne 0 ]; then + echo " execute inference failed" + exit 1 +fi +cal_acc +if [ $? -ne 0 ]; then + echo "calculate accuracy failed" + exit 1 +fi \ No newline at end of file